From d359d0177709a5f888bd951fddd6050b45ef2373 Mon Sep 17 00:00:00 2001 From: Batel Zohar Date: Mon, 24 Nov 2025 20:01:46 +0200 Subject: [PATCH] Adding AratoMCPMock --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index 40053069d6..30ecdda460 100644 --- a/README.md +++ b/README.md @@ -88,6 +88,8 @@ Official integrations are maintained by companies building production ready MCP - Apify Logo **[Apify](https://github.com/apify/apify-mcp-server)** - Use 6,000+ pre-built cloud tools to extract data from websites, e-commerce, social media, search engines, maps, and more - APIMatic Logo **[APIMatic MCP](https://github.com/apimatic/apimatic-validator-mcp)** - APIMatic MCP Server is used to validate OpenAPI specifications using [APIMatic](https://www.apimatic.io/). The server processes OpenAPI files and returns validation summaries by leveraging APIMatic's API. - Apollo Graph Logo **[Apollo MCP Server](https://github.com/apollographql/apollo-mcp-server/)** - Connect your GraphQL APIs to AI agents +- Apollo Graph Logo **[Apollo MCP Server](https://github.com/apollographql/apollo-mcp-server/)** - Connect your GraphQL APIs to AI agents +- Arato Logo **[Arato MCPMock](https://github.com/AratoAi/mcpmock)** - MCPMock is a full-featured Model Context Protocol (MCP) mock server used for developing, testing, and debugging MCP clients and AI agents. - Aqara Logo **[Aqara MCP Server](https://github.com/aqara/aqara-mcp-server/)** - Control [Aqara](https://www.aqara.com/) smart home devices, query status, execute scenes, and much more using natural language. - Archbee Logo **[Archbee](https://www.npmjs.com/package/@archbee/mcp)** - Write and publish documentation that becomes the trusted source for instant answers with AI. Stop cobbling tools and use [Archbee](https://www.archbee.com/) — the first complete documentation platform. - Arize-Phoenix Logo **[Arize Phoenix](https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-mcp)** - Inspect traces, manage prompts, curate datasets, and run experiments using [Arize Phoenix](https://github.com/Arize-ai/phoenix), an open-source AI and LLM observability tool.